Common practice for Webpage prereading in prior art is as follows. The server pre-estimates which files need to be preloaded based on a user's history browsing behavior and Web page typeset in a client, and realizes Web page prereading according to the preloaded files when the user browses Web pages.
US application US2002078165A1 disclosed a smarter prefetching technique that determines whether a user prefers certain sub-pages of the web page and, if so, then prefetches these preferred sub-pages prior to the other sub-pages of the web page. The set of preferred sub-pages is generated by analyzing the user's actions during previous visits to the web page. These learned user preferences include a history of the sub-pages of a web page that have been requested by a user, the number of days back the history should be examined and how many sub-pages within the web page are considered distinct. For example, if a user visits the same news web site every morning and tends to always read the articles in the categories of “politics”, “computing”, “travel” and “books”, then these preferenses will be determined when the news web page was visited. Then those articles will be downloaded into the browser memory before any other categories.
As can be seen, in prior art, it is possible to analyze history visiting behavior of a specific user and then preread Web pages according to his or her preference. This type of prereading has a satisfied success rate only under the premise that the user has visited a portal website/theme website and often visits the website. Such prereading is invalid if the current visited Web page has not been visited or has no preference parameter. Thus, the existing prereading scheme has a very low overall success rate and a very limited range of application.
Also, although it is possible to preread particular subpages in prior art, a user still needs to perform a turning operation on subpages to obtain these subpages from the buffer of the client.